Bibliographic record
Abstract
The eventual topic of this paper is the perhaps grandiose question of whether we have any reason to think that philosophical problems can be solved. Philosophy has been around for quite some time, and its record is cause for pessimism: it is not, exactly, that there are no established results, but that what results there are, are negative (such-and-such is false, or won’t work), or conditional (as Ernest Nagel used to say, “If we had ham, and if we had eggs, then we’d have ham and eggs”).1 I hope in what follows first of all to explain the record. My explanation will naturally suggest a way of turning over a new leaf, and I will wrap up the paper by laying out that proposal and critically assessing its prospects. However, the approach to my topic will have to be roundabout. Along the way, I will detour to consider how the problems of philosophy can be ∗I’m grateful to Jon Bendor, Alice Clapman, Steve Downes, Eyjolfur Emilsson, Christoph Fehige, Richard Gale, Don Garrett, Brian Klug, John MacFarlane, Clif McIntosh, Eddy Nahmias, Ram Neta, Carol Poster, Richard Raatzsch, Peri Schwartz-Shea, Bill Talbott and Mariam Thalos for comments on earlier drafts, and to Michael Bratman, Sarah Buss, Alice Crary, Jenann Ismael, Mark Johnston, Elizabeth Kiss and Alexander Nehamas for helpful discussion. The paper was improved by comments from audiences at Saint Louis University, the CASBS Meta-Historians Discussion Group, the University of Montana, the University of Utah, Kansas State University, Ohio University, Victoria University of Wellington, the University of New South Wales, Oxford University, the University of Alberta, University College Dublin and the University of Bologna. Work on this paper was supported by fellowships from the National Endowment for the Humanities and the Center for Advanced Study in the Behavioral Sciences; I am grateful for the financial support provided through the Center by the Andrew W. Mellon Foundation. Reported by Hilary Putnam (1975, p. 260).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".